Key Responsibilities:
People and Project Leadership:
- Manage the Data Science team, help data scientists take ownership and deliver best outcomes, focusing on quality and productivity
- Will be responsible for supervising, managing, and motivating team members on a day-to-day basis
- Create a framework for communication, project management and execution across team to help drive best practises.
- Implements policies and procedures that will improve operations
- Collaborate closely with stakeholders to understand key result areas, ensure expansion and penetration of data science use-cases
- Develop a pipeline of data science talent and leadership, and contribute to an inclusive community of data analytics practitioners/ thought leaders
- Be able to act proactively to ensure smooth team operations and effective collaboration
Strategic growth and thought leadership:
- Strategize on key opportunities/ whitespaces, drive discussions and expand outcomes from LCCI for data science solutions
- Focus on the future business needs and expand capabilities of the group
- Provide thought leadership on advanced analytics techniques to answer business questions at the intersection of the pharmaceutical and marketing spaces to provide value to commercial teams
Required Skills and Expertise:
- 8+ years of relevant experience in a data science and/ OR people management roles supporting Pharma/Lifesciences Commercial ops internally or in consulting
- At-least 2+ years' experience in leading highly competent and analytics-oriented teams
- Persuasive communication and inter-personal skills
- High level of motivation and a strong desire to find creative solutions to challenging situations
- Demonstrated ability to enforce business rules and policies in a constructive but disciplined manner
- Substantial analytics experience and understanding of complexities in specialty markets, analytics techniques, and US pharmaceutical business
- Proven ability to manage resources to achieve project and business results
- Demonstrated strength/understanding in statistics (preferred)
Education: Master's degree in Computer Applications/ Mathematics/ Pharma or a related field from a premium college
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